The following publications are considered to be relevant for an understanding of the background of the invention:
U.S. Pat. No. 6,252,598;
U.S. Pat. No. 8,166,421 to Magal et al;
WO2005/091125;
WO 2010/086866;
Viola, P et al, Robust Real-time Object Detection, Second International Workshop on Statistical and Computational theories of Vision-Modeling, learning, Computing, and Sampling, Vancouver Canada, Jul. 13, 2001.
Various types of computer control and interface devices exist for inputting commands to a computer. Such devices may for example take the form of a computer mouse, joystick or trackball, wherein a user manipulates the interface device to perform a particular operation such as to select a specific entry from a menu of options, perform a “click” or “point” function, etc. These interface devices require a surface area for placement of the device and, in the case of a mouse, to accommodate device movement and manipulation. In addition, such interface devices are generally connected by a cable to the computer with the cable typically draped across the user's desk, causing obstruction of the user's work area. Manipulation of these interface devices for performing operations is not consistent with common communication gestures, such as the use of a pointing finger hand gesture to select a menu entry, as opposed to maneuvering a mouse until the cursor rests on the desired menu entry.
Attempts have been made to implement hand gesture recognition using optical sensors for use in inputting commands to a device. Gesture recognition requires identifying a body part, typically a hand, in each of a plurality of imagers in a video stream.
For example, it is known to identify hand gestures in a video stream. A plurality of regions in a frame are defined and screened to locate a hand in one of the regions by locating extreme curvature values, such as peaks and valleys, corresponding to predefined hand positions and gestures. The number of peaks and valleys are then used to identify and correlate a predefined hand gesture to the hand image for effectuating a particular computer operation or function.
Systems are also known in which three-dimensional position information is used to identify a gesture created by a body part. At one or more instances of an interval, the posture of a body part is recognized, based on the shape of the body part and its position and orientation. The posture of the body part over each of the one or more instances in the interval is recognized as a combined gesture. The gesture is classified for determining an input into a related electronic device.
User interface methods are also known in which a sequence of depth maps is captured over time of at least a part of a body of a human subject. The depth maps are processed in order to detect a direction and speed of movement of the part of the body as the part of the body passes through an interaction surface. A computer application is controlled responsively to the detected direction and speed.